Audit system on Quality of breast cancer diagnosis and Treatment (QT): results from the survey on screen-detected lesions in Italy, Antonio Ponti, Maria Piera Mano, Vito Distante, Rita Bordon, Luigi Cataliotti, Antonio Federici, Carlo Naldoni, Sabina Pitarella, Marco Rosselli Del Turco, Mario Taffurelli, Mariano Tomatis, Marcello Vettorazzi, Nereo Segnan The final report of the European Society of Mastology (EUSOMA) workshop in Leuven in May 1999 on "Breast Units: future standards and minimum requirements" (Blamey et al., ), states that performance figures on precisely defined quality objectives and outcome measures must be produced by Breast Units yearly. At the same workshop the QT Audit System has been endorsed as the EUSOMA database as it was deemed capable of assisting Breast Units in this activity. QT is a Microsoft Access individual records database produced within the European Breast Cancer Network with funding by the Europe Against Cancer programme of the European Commission, which can be freely downloaded from www.cpo.it/qt or the EUSOMA website (www.eusoma.org). It is available in five languages (English, French, German, Italian, Spanish; an Hungarian version is in preparation) and has users in several European countries. A web version, which would not require the use of Microsoft Access, is under construction. Useful features of QT are that it is being kept updated with guidelines and the availability within the same package of data entry and data analysis facilities, ranging from free analysis with use of the main statistical procedures to the production of several standard reports. QT allows recording of data on all women recalled for assessment in a screening programme (or assessed for clinical suspicion). Data items included in QT are numerous, serving different needs by clinicians which are related not only to monitoring but also to patient care. However, the minimum data set necessary to calculate European indicators is much more limited and is clearly identifiable by the user. QT includes a section with screening history to allow its use for screening evaluation purposes, allowing to classify population breast cancer cases as Never Invited, Never Attenders, Screen Detected, Interval. In addition to the monitoring of process indicators, the system allows data recording and analysis on long term follow up for recurrences and survival. QT has been designed for and is being used by clinical Breast Units for monitoring diagnosis and treatment of breast lesions in symptomatic as well as asymptomatic women. The same database is used by screening programmes for collecting information and calculating quality indicators on the management of screen detected cases. Furthermore, it can assist Cancer Registries for high resolution population studies. The use in different settings in Europe of a common database on breast cancer, reflecting agreed guidelines and benchmarks, can contribute to achieve a greater collaboration and understanding between these different areas of medicine and a better evaluation of the impact of screening and the quality of care. Within the Italian Breast Screening Network (GISMa) a quality assurance programme on treatment of screen detected breast cancers is on going (Distante et al., 2004). Individual data on diagnosis and treatment of screen detected cancers are recorded on QT and reported by local and regional screening programmes to GISMa yearly. In the time period 1997- more than 7,000 lesions treated by 100 surgical Units and detected by 40 screening programmes in 10 Italian Regions have been documented in QT. The definitions of performance indicators which are being monitored are from Italian (FONCaM 2003, Mano et al ) and European (Perry et al., ; Rutgers et al., ) guidelines. Tables 1-6 show a summary of main results related on screen detected cases during - (age 50-69). Table 7 shows time trends 1997-. Running a monitoring system for quality of screening and care requires resources, particularly data managers with some clinical expertise, and an appropriate organisation for collecting data and making the best use of them. An individual, be it a physician, a breast nurse or a data manager should be made responsible for co-ordinating data collection and reporting at the
screening programme evaluation Unit as well as at each Breast Unit collaborating with the programme. For auditing to produce change, feed back and careful analysis of emerging problems is necessary, and the best setting for these activities is multidisciplinary meetings. Although many of the indicators relate to individual skill or knowledge of recommendations, most involve the team as well. Discussion of data analysis reports during multidisciplinary meetings often prompts improvement of quality of data itself, such as reduction of missing values and accurate item definition, classification and coding. References 1. Blamey R., Blichert-Toft M., Cataliotti L. et al. Breast Units: Future Standards and Minimum Requirements. Eur J Cancer,, 36, 2288-2293. 2. Distante V., Mano M.P., Ponti A. Monitoring surgical treatment of screen-detected breast lesions in Italy. Eur J Cancer 2004, 40, 1006-10012. 3. Forza Operativa Nazionale sul Carcinoma Mammario. I Tumori della Mammella, Linee Guida sulla diagnosi, il trattamento e la riabilitazione, 2003. 4. Mano M.P., Distante V., Ponti A., Segnan N., Bordon R., Simoncini R., Cataliotti L. e il Gruppo GISMa sul Trattamento. Monitoraggio e Promozione della Qualità del Trattamento del carcinoma mammario nelle Unità di Senologia e nei programmi di screening in Italia. Attualità di Senologia, Supplemento 1,. 5. Perry N., Blichert-Toft M., Cataliotti L. et al. Quality Assurance in the Diagnosis of Breast Disease, Eur J Cancer,, 37, 159-172. 6. Rutgers E.J.T., Bartelink H., Blamey R. et al. Quality Control in Locoregional Treatment for Breast Cancer. Eur J Cancer,, 37, 447-453. 2
Table 1: GISMa survey ; distribution of cases (operated screen-detected lesions) by Region. 156 cases are excluded from subsequent analyses because not submitted on time. Number of cases Number of programmes Piemonte and Valle d Aosta 812 10 Veneto 270 12 Emilia Romagna 819 10 Toscana 151 1 Umbria 33 1 Lazio 128 3 Sicilia 36 2 TOTALE 2,249 39 Table 2: GISMa -; distribution by final histopathology diagnosis. N N N Benign 302 18.5 354 18.7 335 16.0 In situ 185 11.3 224 11.9 300 14.3 Microinvasive 29 1.8 48 2.5 50 2.4 Invasive 1,103 67.5 1,234 65.3 1,327 63.4 Unknown 5 0.3 30 1.6 81 3.8 TOTAL 1,635 100 1,890 100 2,093 100 3
Table 3: Summary on diagnostic indicators, GISMa (1,635 cases), (1,890 cases) e (2,093 cases) Indicator Target Number of diagnostic sessions 3-99.8 99.3 95 Number of diagnostic sessions (including screening test) 3-96.2 89.0 95 Pre-operative diagnosis in cancers (C4-5,B4-5) 73.7 75.8 81.0 - Pre-operative diagnosis in cancers (C5,B5) 53.8 57.6 59.8 70 Non-inadequate cytology if final diagnosis is cancer 92.2 89.6 91.7 85 Absolute sensitivity C5 54.9 56.6 56.1 60 Grade available 97.3 99.0 99.0 95 Estrogen receptors available 98.3 98.9 97.5 95 Waiting time for surgery from prescription 30 days 65.8 55.5 60.1 80 Waiting time for surgery from screening test 60 days 65.9 56.5 58.2-4
Table 4: Summary on surgical indicators, GISMa (1.635 cases), (1.890 cases) e (2.093 cases) Indicator Target Correct excision 98.6 99.5 98.6 95 Frozen section not performed in cancers 10 mm 49.1 55.2 61.9 95 Only one operation after pre-operative diagnosis 92.9 94.2 90.9 90 Conservative surgery in invasive cancers 20 mm 91.0 91.0 88.8 80 Conservative surgery in situ cancers 20 mm 92.7 89.1 89.0 80 Margins > 1 mm after last surgery 88.4 88.0 94.0 95 SLN, identification rate (combined technique) - - 95.9 90 SLN, identification rate (blue dye) - - 93.2 90 SLN, identification rate (isotope) - - 95.6 90 Number lymph nodes > 9 in axillary dissection 91.9 94.0 93.9 95 No dissection in DCIS 80.4 90.4 92.0 95 Immediate reconstruction after mastectomy 29.8 30.1 40.2-5
Table 5: GISMa -; utilisation of frozen section in lesions with pre-operative diagnosis. Pre-operative diagnosis C5 or B5 43.0 26.6 23.0 B5 only 33.3 19.8 9.4 6
Table 6: GISMa -; number of eligible cases and proportion of missing values. Indicator Eligible cases Eligible cases Eligible cases Missing Missing Missing Number of diagnostic sessions 3-1,815 1,641-6.9 9.6 Number of diagnostic sessions (including screening test) 3-1,815 1,641-6.9 9.6 Pre-operative diagnosis in cancers (C5,B5) 1,308 1,461 1,668 9.2 5.8 5.8 Non-inadequate cytology if final diagnosis is cancer 944 1,061 1,277 2.8 1.9 2.0 Absolute sensitivity C5 960 1,078 1,294 2.8 1.9 1.9 Correct excision 761 975 1,186 23.6 22.6 19.7 Frozen section not performed in cancers 10 mm 364 430 434 4.9 6.1 7.6 Only one operation after pre-operative diagnosis 620 803 915 6.9 4.2 3.4 Conservative surgery in invasive cancers 20 mm 662 808 871 4.8 9.0 5.2 Conservative surgery in situ cancers 20 mm 120 174 210 6.7 5.2 4.8 Margins >1 mm after last surgery 900 1,109 1,257 6.0 10.5 14.1 SLN, identification rate (combined technique) - 29 110-69.0 11.8 SLN, identification rate (blue dye) - 60 155-58.3 24.5 SLN, identification rate (isotope) - 178 439-71.9 11.6 Number lymph nodes >9 in axillary dissection 828 718 712 1.2 2.2 2.8 No dissection in DCIS 169 207 280 3.5 6.8 6.8 Immediate reconstruction after mastectomy 228 221 320 13.7 20.4 15.3 Grade available 1,068 1,189 1,285 7.9 10.5 20.0 Estrogen receptors available 1,068 1,189 1,285 10.5 10.7 5.7 Waiting time for surgery from prescription 30 days 1,529 1,877 1,941 32.8 30.6 20.0 Waiting time for surgery from screening test 60 days 1,446 1,848 1,910 33.7 27.7 28.3 7
Table 7: GISMa 1997-. Time trends for selected indicators 1. 1997 1998 1999 Target Pre-operative diagnosis in cancers (C4-5,B4-5)) 67.6 72.6 74.9 78.7 81.3 82.0 - Correct excision 98.6 98.3 99.5 97.9 99.0 99.4 95 Frozen section not performed in cancers 10 mm 53.3 65.2 60.0 48.8 58.7 68.5 95 Conservative surgery in invasive cancers 20 mm 88.9 93.2 92.9 90.2 93.4 91.7 80 Conservative surgery in situ cancers 20 mm 87.0 97.1 92.9 91.0 88.7 91.8 80 Number lymph nodes > 9 in axillary dissection 94.1 93.9 92.0 90.7 92.4 92.6 95 No dissection in DCIS 92.1 85.7 90.0 79.7 96.0 96.9 95 Waiting time for surgery from prescription 21 days 56.1 51.1 33.3 37.0 22.7 32.3-1 Only programmes contributing data for the whole time period are included. 8